American Journal of Preventive Cardiology (Sep 2024)

THE BURDEN OF CARDIO-METABOLIC DISORDERS, SUBSTANCE ABUSE AND PREDICTORS OF MORTALITY IN PATIENTS UNDERGOING RENAL TRANSPLANT: A POPULATION-BASED RETROSPECTIVE STUDY

  • Ambica Vivek Nair, MD

Journal volume & issue
Vol. 19
p. 100846

Abstract

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Therapeutic Area: ASCVD/CVD Risk Factors Background: Cardio-metabolic disorders (CMBD), encompass a spectrum of diseases including hypertension, diabetes, hyperlipidemia, obesity, stroke. They significantly impact healthcare systems globally. The impact of CMBD on patients undergoing renal transplant is of particular interest as it might be associated with a higher risk of adverse outcomes. In this study we aim to investigate the burden of CMBD in patients undergoing renal transplant and any associated predictors of mortality. Methods: Utilizing National Inpatient Database records (2016-2021), this study identifies kidney transplant recipients, excluding others with precise ICD-10 coding, to explore cardiovascular comorbidities' impact. Statistical methods include t-tests, Pearson's chi-square, and multivariate mixed-effect logistic regression for comprehensive analysis. Results: Of the 646,695 patients identified who had undergone kidney transplant, Caucasian (55.4%) males (56.2%) formed the majority. 39.1% of patients undergoing transplant had underlying hypertension while 14.5% had complicated hypertension. 56.5% had dyslipidemia while 85.5% were obese. Smoking was prevalent in 77.5% of the study population whereas alcohol abuse was prevalent in 98.7% of patients undergoing kidney transplantation. While 88.1% had diabetes, 55.33% had diabetes associated with major complications. Underlying pulmonary and liver disease were direct predictors of mortality with increased incidence of in-hospital deaths while patients who were obese had lower mortality rates. Conclusions: There is a significantly high prevalence of baseline cardiovascular comorbidities in patients undergoing kidney transplant. Although none of the CMBD were direct predictors of mortality, proper optimization of these risk factors is essential to optimize medical outcomes.